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We assembled genome-wide data from 271 ancient Iberians, of whom 176 are from the largely unsampled period after 2000 BCE, thereby providing a high-resolution time transect of the Iberian Peninsula.We document high genetic substructure between northwestern and southeastern hunter-gatherers before the spread of farming.We reveal sporadic contacts between Iberia and North Africa by ~2500 BCE and, by ~2000 BCE, the replacement of 40% of Iberia’s ancestry and nearly 100% of its Y-chromosomes by people with Steppe ancestry.We show that, in the Iron Age, Steppe ancestry had spread not only into Indo-European–speaking regions but also into non-Indo-European–speaking ones, and we reveal that present-day Basques are best described as a typical Iron Age population without the admixture events that later affected the rest of Iberia. Additionally,we document how, beginning at least in the Roman period, the ancestry of the peninsula was transformed by gene flow from North Africa and the eastern Mediterranean.
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POPULATION GENETICS
The genomic history of the Iberian
Peninsula over the past 8000 years
Iñigo Olalde
1
*, Swapan Mallick
1,2,3
, Nick Patterson
2
, Nadin Rohland
1
,
Vanessa Villalba-Mouco
4,5
, Marina Silva
6
, Katharina Dulias
6
, Ceiridwen J. Edwards
6
,
Francesca Gandini
6
, Maria Pala
6
, Pedro Soares
7
, Manuel Ferrando-Bernal
8
,
Nicole Adamski
1,3
, Nasreen Broomandkhoshbacht
1,3
, Olivia Cheronet
9
,
Brendan J. Culleton
10
, Daniel Fernandes
9,11
, Ann Marie Lawson
1,3
,
Matthew Mah
1,2,3
, Jonas Oppenheimer
1,3
, Kristin Stewardson
1,3
, Zhao Zhang
1
,
Juan Manuel Jiménez Arenas
12,13,14
, Isidro Jorge Toro Moyano
15
,
Domingo C. Salazar-García
16
, Pere Castanyer
17
, Marta Santos
17
, Joaquim Tremoleda
17
,
Marina Lozano
18,19
, Pablo García Borja
20
, Javier Fernández-Eraso
21
,
José Antonio Mujika-Alustiza
21
, Cecilio Barroso
22
, Francisco J. Bermúdez
22
,
Enrique Viguera Mínguez
23
, Josep Burch
24
, Neus Coromina
24
, David Vivó
24
,
Artur Cebrià
25
, Josep Maria Fullola
25
, Oreto García-Puchol
26
, Juan Ignacio Morales
25
,
F. Xavier Oms
25
, Tona Majó
27
, Josep Maria Vergès
18,19
, Antònia Díaz-Carvajal
28
,
Imma Ollich-Castanyer
28
, F. Javier López-Cachero
25
, Ana Maria Silva
29,30,31
,
Carmen Alonso-Fernández
32
, Germán Delibes de Castro
33
, Javier Jiménez Echevarría
32
,
Adolfo Moreno-Márquez
34,35
, Guillermo Pascual Berlanga, Pablo Ramos-García
36
,
José Ramos-Muñoz
34
, Eduardo Vijande Vila
34
, Gustau Aguilella Arzo
37
,
Ángel Esparza Arroyo
38
, Katina T. Lillios
39
, Jennifer Mack
40
, Javier Velasco-Vázquez
41
,
Anna Waterman
42
, Luis Benítez de Lugo Enrich
43,44
, María Benito Sánchez
45
,
Bibiana Agustí
46,47
, Ferran Codina
47
, Gabriel de Prado
47
, Almudena Estalrrich
48
,
Álvaro Fernández Flores
49
, Clive Finlayson
50,51,52,53
, Geraldine Finlayson
50,52,53
,
Stewart Finlayson
50,54
, Francisco Giles-Guzmán
50
, Antonio Rosas
55
,
Virginia Barciela González
56,57
, Gabriel García Atiénzar
56,57
, Mauro S. Hernández Pérez
56,57
,
Armando Llanos
58
, Yolanda Carrión Marco
59
, Isabel Collado Beneyto
60
,
David López-Serrano
61
, Mario Sanz Tormo, António C. Valera
62
, Concepción Blasco
43
,
Corina Liesau
43
, Patricia Ríos
43
, Joan Daura
25
, María Jesús de Pedro Michó
63
,
Agustín A. Diez-Castillo
64
, Raúl Flores Fernández, Joan Francès Farré
65
,
Rafael Garrido-Pena
43
, Victor S. Gonçalves
30
, Elisa Guerra-Doce
33
,
Ana Mercedes Herrero-Corral
66
, Joaquim Juan-Cabanilles
67
, Daniel López-Reyes
68
,
Sarah B. McClure
69
, Marta Merino Pérez
70
, Arturo Oliver Foix
37
,
Montserrat Sanz Borràs
25
, Ana Catarina Sousa
30
, Julio Manuel Vidal Encinas
71
,
Douglas J. Kennett
10,69
, Martin B. Richards
6
, Kurt Werner Alt
72,73
,
Wolfgang Haak
4,74
, Ron Pinhasi
9
, Carles Lalueza-Fox
8
*, David Reich
1,2,3
*
We assembled genome-wide data from 271 ancient Iberians, of whom 176 are from the
largely unsampled period after 2000 BCE, thereby providing a high-resolution time transect
of the Iberian Peninsula.We document high genetic substructure between northwestern
and southeastern hunter-gatherers before the spread of farming. We reveal sporadic
contacts between Iberia and North Africa by ~2500 BCE and, by ~2000 BCE, the
replacement of 40% of Iberias ancestry and nearly 100% of its Y-chromosomes by people
with Steppe ancestry. We show that, in the Iron Age, Steppe ancestry had spread not only
into Indo-Europeanspeaking regions but also into non-Indo-Europeanspeaking ones, and
we reveal that present-day Basques are best described as a typical Iron Age population
without the admixture events that later affected the rest of Iberia. Additionally,we document
how, beginning at least in the Roman period, the ancestry of the peninsula was transformed
by gene flow from North Africa and the eastern Mediterranean.
The Iberian Peninsula, lying at the extreme
southwestern corner of Europe, provides
an excellent context in which to assess the
final impact of population movements en-
tering the continent from the east as well
as interactions with North Africa. To study the
genetic impact of prehistoric and historic events
in Iberia, we prepared next-generation sequenc-
ing libraries treated with uracil-DNA glycosylase
(UDG) (1) and enriched them for ~1.2 million
single-nucleotide polymorphisms (SNPs) (2,3)
to generate genome-wide data from 4 Mesolithic,
44 Neolithic, 47 Copper Age, 53 Bronze Age,
24 Iron Age, and 99 historical-period Iberians
(Fig.1,AandB,andtablesS1andS2).Wealso
generated 26 radiocarbon dates (table S3). We
co-analyzed the new genomic data with previ-
ously reported data from 1107 ancient individ-
uals, including 132 from Iberia (Fig. 1B) (2,49),
and 2862 present-day individuals (10). We filtered
fromtheanalysisdatasetsindividualscoveredby
<10,000 SNPs, with evidence of contamination,
or first-degree relatives of others (table S1). We
analyzed the data with principal components
analysis (PCA) (Fig. 1, C and D), f-statistics (11),
and qpAdm (12) and summarize the results in
Fig. 1E. We confirmed the robustness of key
findings by repeating analyses after remov-
ing SNPs in CpG dinucleotides (table S5) that
are susceptible to cytosine-to-thymine errors
even in UDG-treated libraries (1).
Previous knowledge of the genetic structure
of Mesolithic Iberia comes from three individ-
uals from the northwest: LaBraña1 (2), Canes1
(5), and Chan (5). We add LaBraña2, who was a
brother of the previously reported LaBraña1
(figs. S1 and S2 and table S6), as well as Cueva
de la Carigüela (fig. S10), Cingle del Mas Nou,
and Cueva de la Cocina from the southeast. In
northwest Iberia, we document a previously un-
appreciated ancestry shift before the arrival of
farming (Fig. 2A, fig. S5, and table S7). The oldest
individual Chan was similar to the ~19,000-year-old
El Mirón, whereas the La Braña brothers from
~1300 years later were close r to central European
hunter-gatherers like the Hungarian KO1, with
an even more extreme shift ~700 years later in
Canes1. This likely reflects gene flow affecting
northwest Iberia but not the southeast, where
individuals remained close to El Mirón (Fig. 2A).
More data from the Mesolithic period, especially
from currently unsampled areas, would provide
additional insight into the geographical impact
and archaeological correlates of this ancestry shift.
For the Neolithic and Copper Age, we model
populationsasmixturesofgroupsrelatedto
Anatolian Neolithic, El Mirón, and KO1 (Fig. 2A
and table S8). We replicate previous findings of
the arrival of Anatolian Neolithicassociated an-
cestry in multiple regions of Iberia in the Early
Neolithic (7,8,12); however, sampling from this
period remains limited and studies of larger sam-
ple sizes and additional sites will be important
to shed further light on the interaction between
the incoming farmers and indigenous hunter-
gatherers. For the Middle Neolithic and Copper
Age, we reproduce previous reports of an in-
crease of hunter-gathererrelated ancestry after
4000 BCE (6,7,12,13), with higher proportions
in groups from the north and center. Using our
observations about population substructure in
theMesolithicasareferenceframe,weshowthat
the hunter-gathererrelated ancestry during those
periods was more closely related to later north-
western (Canes1-like) hunter-gatherers than to
the El Mirónlike hunter-gatherers (Fig. 2A), pro-
viding clues about the source of this ancestry.
Our Copper Age dataset includes a newly re-
ported male (I4246) from Camino de las Yeseras
(14) in central Iberia, radiocarbon dated to
24732030 calibrated years BCE, who clusters
with modern and ancient North Africans in the
PCA (Fig. 1C and fig. S3) and, like ~3000 BCE
Moroccans (8), can be well modeled as having
ancestry from both Late Pleistocene North Africans
(15)andEarlyNeolithicEuropeans(tablesS9and
S10). His genome-wide ancestry and uniparental
RESEARCH
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markers (tables S1 and S4) are unique among
Copper Age Iberians, including individuals from
sites with many analyzed individuals such as
Sima del Ángel, and point to a North African
origin. Our genetic evidence of sporadic contacts
with North Africa during the Copper Age fits
with the presence of African ivory at Iberian
sites (16) and is further supported by a Bronze
Age individual (I7162) from Loma del Puerco
in southern Iberia who had 25% ancestry re-
lated to individuals like I4246 (Fig. 1D and
table S16). However, these early movements
from North Africa had a limited impact on
Copper and Bronze Age Iberians, as North
African ancestry only became widespread in
the past ~2000 years.
FromtheBronzeAge(~2200900 BCE), we
increase the available dataset (6,7,17) from 7 to
60 individuals and show how ancestry from the
Pontic-Caspian steppe (Steppe ancestry) appeared
throughout Iberia in this period (Fig. 1, C and D),
albeit with less impact in the south (table S13).
The earliest evidence is in 14 individuals dated to
~25002000 BCE who coexisted with local people
without Steppe ancestry (Fig. 2B). These groups
lived in close proximity and admixed to form
the Bronze Age population after 2000 BCE with
~40% ancestry from incoming groups (Fig. 2B
and fig. S6). Y-chromosome turnover was even
more pronounced (Fig. 2B), as the lineages com-
mon in Copper Age Iberia (I2, G2, and H) were
almost completely replaced by one lineage, R1b-
M269.Thesepatternspointtoahighercon-
tribution of incoming males than females, also
supported by a lower proportion of nonlocal an-
cestry on the X-chromosome (table S14 and fig.
S7), a paradigm that can be exemplified by a
Bronze Age tomb from Castillejo del Bonete
containing a male with Steppe ancestry and a
femalewithancestrysimilartoCopperAge
Iberians. Although ancient DNA can document
that sex-biased admixture occurred, archaeolog-
ical and anthropological research will be needed
to understand the processes that generated it.
For the Iron Age, we document a consistent
trend of increased ancestry related to Northern
and Central European populations with respect
to the preceding Bronze Age (Figs. 1, C and D,
and 2B). The increase was 10 to 19% (95% con-
fidence intervals given here and in the percent-
ages that follow) in 15 individuals along the
Mediterranean coast where non-Indo-European
Iberian languages were spoken; 11 to 31% in two
individuals at the Tartessian site of La Angorrilla
in the southwest with uncertain language attri-
bution; and 28 to 43% in three individuals at
La Hoya in the north where Indo-European
Celtiberian languages were likely spoken (fig. S6
and tables S11 and S12). This trend documents
gene flow into Iberia during the Late Bronze
Age or Early Iron Age, possibly associated with
the introduction of the Urnfield tradition (18).
Unlike in Central or Northern Europe, where
Steppe ancestry likely marked the introduction
of Indo-European languages (12), our results
indicate that, in Iberia, increases in Steppe an-
cestry were not always accompanied by switches
to Indo-European languages. This is consistent
with the genetic profile of present-day Basques
whospeaktheonlynon-Indo-Europeanlanguage
in Western Europe but overlap genetically with
Iron Age populations (Fig. 1D) showing substan-
tial levels of Steppe ancestry.
In the historical period, our transect begins
with 24 individuals from the 5th century BCE
to the 6th century CE from the Greek colony of
Empúries in the northeast (19)whofallinto
two main ancestry groups (Fig. 1, C and D, and
fig. S8): one similar to Bronze Age individuals
from the Aegean, and the other similar to Iron
AgeIberianssuchasthosefromthenearbynon-
Greek site of Ullastret, confirming historical
sources indicating that this town was inhabited
by a multiethnic population (19). The impact of
mobility from the central/eastern Mediterra-
nean during the Classical period is also evident
in 10 individuals from the 7th to 8th century CE
site of L'Esquerda in the northeast, who show
a shift from the Iron Age population in the
direction of present-day Italians and Greeks (Fig.
1D) that accounts for approximately one-quarter
of their ancestry (Fig. 2C and table S17). The same
shift is also observed in present-day Iberians
outside the Basque area and is plausibly a
consequence of the Roman presence in the pe-
ninsula, which had a profound cultural impact
and, according to our data, a substantial genetic
impact too.
In contrast to the demographic changes in the
Classical period, movements into Iberia during the
decline of the Roman Empire had less long-term
demographic impact. Nevertheless, individual
sitesfor example, the 6th century site of Pla de
l'Horta in the northeastbear witness to events
in this period. These individuals, archaeologically
Olalde et al., Science 363, 12301234 (2019) 15 March 2019 2of5
1
Department of Genetics, Harvard Medical School, Boston, MA, USA.
2
Broad Institute of MIT and Harvard, Cambridge, MA, USA.
3
Howard Hughes Medical Institute, Harvard Medical School,
Boston, MA, USA.
4
Max Planck Institute for the Science of Human History, Jena, Germany.
5
Departamento de Ciencias de la Antigüedad, Grupo Primeros Pobladores del Valle del Ebro
(PPVE), Instituto de Investigación en Ciencias Ambientales (IUCA), Universidad de Zaragoza, Zaragoza, Spain.
6
Department of Biological and Geographical Sciences, School of Applied Sciences,
University of Huddersfield, Huddersfield, UK.
7
Centre of Molecular and Environmental Biology, Department of Biology, University of Minho, Braga, Portugal.
8
Institute of Evolutionary Biology,
CSIC-Universitat Pompeu Fabra, Barcelona, Spain.
9
Department of Evolutionary Anthropology, University of Vienna, Vienna, Austria.
10
Department of Anthropology and Institutes of Energy and
the Environment, The Pennsylvania State University, University Park, PA, USA.
11
Research Center for Anthropology and Health, Department of Life Science, University of Coimbra, Coimbra,
Portugal.
12
Departamento de Prehistoria y Arqueología, Universidad de Granada, Granada, Spain.
13
Instituto Universitario de la Paz y los Conflictos, Universidad de Granada, Granada, Spain.
14
Department of Anthropology - Anthropologisches Institut and Museum, Universität Zürich, Zürich, Switzerland.
15
Museo Arqueológico y Etnológico de Granada, Granada, Spain.
16
Departamento
de Geografía, Prehistoria y Arqueología, Grupo de Investigación en Prehistoria, (UPV-EHU)/IKERBASQUE-Basque Foundation for Science, Vitoria, Spain.
17
Museu d'Arqueologia de Catalunya-
Empúries, L'Escala, Spain.
18
Institut Català de Paleoecologia Humana i Evolució Social (IPHES), Tarragona, Spain.
19
Àrea de Prehistòria, Universitat Rovira i Virgili (URV), Tarragona, Spain.
20
Departamento de Prehistoria e Historia Antigua, Universidad Nacional de Educación a Distancia, Valencia, Spain.
21
Departamento de Geografía, Prehistoria y Arqueología, Universidad del País
Vasco, Vitoria, Spain.
22
Fundación Instituto de Investigación de Prehistoria y Evolución Humana (FIPEH), Lucena, Spain.
23
Área de Genética, Facultad de Ciencias, Universidad de Málaga, Málaga,
Spain.
24
Institut de Recerca Històrica, Universitat de Girona, Girona, Spain.
25
SERP, Departament dHistòria i Arqueologia, Facultat de Geografia i Història, Universitat de Barcelona, Barcelona,
Spain.
26
PREMEDOC Research Group, Departament de Prehistòria, Arqueologia i Historia Antiga, Universitat de València, València, Spain.
27
Archaeom. Departament de Prehistòria, Universitat
Autònoma de Barcelona, Cerdanyola del Vallès, Spain.
28
Universitat de Barcelona-GRAMP/Museu Arqueològic de l'Esquerda, Roda de Ter, Spain.
29
Laboratory of Prehistory, Research Center for
Anthropology and Health, Department of Life Sciences, University of Coimbra, Coimbra, Portugal.
30
UNIARQ, Faculdade de Letras, Universidade de Lisboa, Lisboa, Portugal.
31
CEF, Department of
Life Sciences, University of Coimbra, Coimbra, Portugal.
32
Cronos S.C. Arqueología y Patrimonio, Burgos, Spain.
33
Departamento de Prehistoria, Facultad de Filosofía y Letras, Universidad de
Valladolid, Valladolid, Spain.
34
Departamento de Historia, Geografía y Filosofía, Universidad de Cádiz, Cádiz, Spain.
35
Departamento de Geografía, Historia y Humanidades, Universidad de Almería,
Almería, Spain.
36
School of Dentistry, University of Granada, Granada, Spain.
37
Servicio de Investigaciones Arqueológicas y Prehistóricas de la Diputación de Castellón, Castelló de la Plana, Spain.
38
GIR PrehUSAL, Departamento de Prehistoria, Historia Antigua y Arqueología, Universidad de Salamanca, Salamanca, Spain.
39
Department of Anthropology, University of Iowa, Iowa City, IA,
USA.
40
Office of the State Archaeologist, University of Iowa, Iowa City, IA, USA.
41
Departamento de Ciencias Históricas, Universidad de Las Palmas de Gran Canaria, Las Palmas, Spain.
42
Mt. Mercy University, Cedar Rapids, IA, USA.
43
Departamento de Prehistoria y Arqueología, Universidad Autónoma de Madrid, Madrid, Spain.
44
Departamento de Prehistoria y Arqueología,
Universidad Nacional de Educación a Distancia, Madrid, Spain.
45
Departamento de Medicina Legal, Psiquiatría y Anatomía Patológica, Universidad Complutense de Madrid, Madrid, Spain.
46
INSITU S.C.P., Centelles, Spain.
47
Museu d'Arqueologia de Catalunya-Ullastret, Ullastret, Spain.
48
Instituto Internacional de Investigaciones Prehistóricas de Cantabria IIIPC (Universidad de
Cantabria-Gobierno de Cantabria-Santander), Santander, Spain.
49
Arqueología y Gestión S.L.L., Fuentes de Andalucia, Spain.
50
The Gibraltar National Museum, Gibraltar.
51
Department of
Anthropology, University of Toronto, Toronto, ON, Canada.
52
School of Natural Sciences and Psychology, Liverpool John Moores University, Liverpool, UK.
53
Institute of Life and Earth Sciences,
University of Gibraltar, Gibraltar.
54
Department of Life Sciences, Anglia Ruskin University, Cambridge, UK.
55
Paleoanthropology Group, Department of Paleobiology, Museo Nacional de Ciencias
Naturales (MNCN)Consejo Superior de Investigaciones Científicas (CSIC), Madrid, Spain.
56
Departamento de Prehistoria, Arqueología e Historia Antigua, Facultad de Filosofía y Letras,
Universidad de Alicante, San Vicente del Raspeig, Spain.
57
Instituto Universitario de Investigación en Arqueología y Patrimonio Histórico (INAPH), San Vicente del Raspeig, Spain.
58
Instituto
Alavés de Arqueología, Vitoria-Gasteiz, Spain.
59
Departament de Prehistòria, Arqueologia i Historia Antiga, Universitat de València, València, Spain.
60
Museu Arqueológic Vicent Casanova,
Bocairent, Spain.
61
Estrats, Treballs d'Arqueologia SL, El Campello, Spain.
62
Era Arqueologia, Oeiras, Portugal.
63
Museu de Prehistòria de València, València, Spain.
64
GRAM Research Group,
Departament de Prehistòria, Arqueologia i Historia Antiga, Universitat de València, València, Spain.
65
Museu i Poblat Ibèric de Ca n'Oliver, Cerdanyola del Vallès, Spain.
66
Departamento de
Prehistoria, Universidad Complutense de Madrid, Madrid, Spain.
67
Museu de Prehistoria/SIP, Diputació de València, València, Spain.
68
Arqueovitis sccl., Avinyonet del Penedès, Spain.
69
Department of Anthropology, University of California, Santa Barbara, CA, USA.
70
Unitat d'Antropologia Física, Departament de Biologia Animal, Facultat de Biologia, Universitat de Barcelona,
Barcelona, Spain.
71
Junta de Castilla y León, Servicio de Cultura de León, León, Spain.
72
Center of Natural and Cultural Human History, Danube Private University, Krems, Austria.
73
Department
of Biomedical Engineering and Integrative Prehistory and Archaeological Science, Basel University, Basel, Switzerland.
74
School of Biological Sciences, University of Adelaide, Adelaide, Australia.
*Corresponding author. Email: inigo_olalde@hms.harvard.edu (I.O.); carles.lalueza@upf.edu (C.L.-F.); reich@genetics.med.harvard.edu (D.R.) Independent researcher.
RESEARCH |REPORT
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interpreted as Visigoths, are shifted from those
at L'Esquerda in the direction of Northern and
Central Europe (Figs. 1D and 2C and table S18),
and we observe the Asian mitochondrial DNA
(mtDNA) haplogroup C4a1a also found in Early
Medieval Bavaria (20), supporting a recent link
to groups with ancestry originally derived from
Central and Eastern Europe.
In the southeast, we recovered genomic data
from 45 individuals dated between the 3rd and
16th centuries CE. All analyzed individuals fell
outside the genetic variation of preceding Iberian
Iron Age populations (Fig. 1, C and D, and fig.
S3) and harbored ancestry from both Southern
European and North African populations (Fig.
2D), as well as additional Levantine-related
ancestry that could potentially reflect ancestry
from Jewish groups (21). These results demon-
strate that by the Roman period, southern Iberia
had experienced a major influx of North African
ancestry, probably related to the well-known
mobility patterns during the Roman Empire
(22) or to the earlier Phoenician-Punic pres-
ence (23);thelatterisalsosupportedbythe
observation of the Phoenician-associated Y-
chromosome J2 (24). Gene flow from North
Africa continued into the Muslim period, as
is clear from Muslim burials with elevated North
African and sub-Saharan African ancestry (Fig.
2D, fig. S4, and table S22) and from uniparental
markers typical of North Africa not present
among pre-Islamic individuals (Fig. 2D and
fig. S11). Present-day populations from south-
ern Iberia harbor less North African ancestry
(25) than the ancient Muslim burials, plausi-
bly reflecting expulsion of moriscos (former
Muslims converted to Christianity) and repo-
pulation from the north, as supported by histor-
ical sources and genetic analysis of present-day
groups (25). The impact of Muslim rule is also
evident in northeast Iberia in seven individu-
als from Sant Julià de Ramis from the 8th to
12th centuries CE who, unlike previous ancient
individuals from the same region, show North
Africanrelated ancestry (Fig. 2C and table S19)
and a complete overlap in PCA with present-day
Iberians (Fig. 1D).
Our time transect allowed us to track frequen-
cy changes of phenotypically important variants
over the past 4000 years (fig. S9), a period that
has been minimally sampled in the ancient DNA
literature not just in Iberia but in Europe more
generally. Before this work, it was known that
the lactase persistence allele at rs4988235, which
is present at moderate or high frequencies in
most European populations today and is one of
the strongest known signals of selection in
Europeans (26), occurred at extremely low fre-
quencies in Europe through the Bronze Age (2),
raising the question of when it became common.
Olalde et al., Science 363, 12301234 (2019) 15 March 2019 3of5
Fig. 1. Overview of the ancient Iberian genetic time transect. (A)
Geographic distribution and (B) dates of new and previously reported
samples. Random jitter is added for sites with multiple individuals. Sites
mentioned in the text are labeled. (C) PCA of 989 present-day west
Eurasian individuals (gray dots), with ancient individuals from Iberia and
other regions (pale yellow) projected onto the first two principal
components. (D) Section of the PCA in (C) marked with the dashed box.
(E) Schematic representation of events documented in this study.
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Here we show that in Iberia, the allele continued
to occur at low frequency in the Iron Age (fig. S9)
and only approached present-day frequencies in
the past 2000 years, pointing to recent strong
selection.
Beyond the specific insights about Iberia, this
study serves as a model for how a high-resolution
ancient DNA transect continuing into historical
periods can be used to provide a detailed descrip-
tion of the formation of present-day populations
(Fig. 1E); future application of similar strategies
will provide equally valuable insights in other
world regions.
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Fig. 2. Genome-wide admixture proportions using qpAdm.(A) Modeling
Mesolithic, Neolithic, and Copper Age populations as a mixture of Anatolian
Neolithic, El Mirón, and KO1. Percentages indicate proportion of El Mirón +
KO1 ancestry. (B) Proportion of ancestry derived from central European
Beaker/Bronze Age populations in Iberians from the Middle Neolithic to the
Iron Age (table S15). Colors indicate the Y-chromosome haplogroup for each male
(table S4). (C) Ancestry proportions for individuals from three sites in northeast
Iberia dated between the 6th and 12th centuries CE. nrepresents the number of
individuals analyzed in each site. (D) Ancestry proportions for individuals from
southeast Iberia from the 3rd to 16th centuries CE (tables S20 and S21). Each bar
represents one individual, with associated mtDNA (top) and Y-chromosome
(bottom). Haplogroups with a likely recent nonlocal origin are bold.
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ACKNOWL EDGMEN TS
We thank I. Mathieson, M. Lipson, I. Lazaridis, J. Sedig, and K. Sirak
for discussions, and M. E. Allentoft, K.-G. Sjögren, K. Kristiansen,
and E. Willerslev for facilitating sample collection. We thank
M. Meyer for sharing the optimized oligo sequences for
single-stranded library preparation. We thank the different museums
(listed in the supplementary materials) for permission to study
archaeological remains. Funding: J.M.F., F.J.L.-C., J.I.M., F.X.O., J.D.,
and M.S.B. were supported by HAR2017-86509-P, HAR2017-87695-P,
and SGR2017-11 from the Generalitat de Catalunya, AGAUR
agency. C.L.-F. was supported by Obra Social La Caixa and by
FEDER-MINECO (BFU2015- 64699-P). L.B.d.L.E. was supported by
REDISCO-HAR2017-88035-P (Plan Nacional I+D+I, MINECO). C.L.,
P.R., and C.Bl. were supported by MINECO (HAR2016-77600-P).
A.Esp., J.V.-V., G.D., and D.C.S.-G. were supported by MINECO
(HAR2009-10105 and HAR2013-43851-P). D.J.K. and B.J.C. were
supported by NSF BCS-1460367. K.T.L., A.W., and J.M. were
supported by NSF BCS-1153568. J.F.-E. and J.A.M.-A. were supported
by IT622-13 Gobierno Vasco, Diputación Foral de Álava, and
Diputación Foral de Gipuzkoa. We acknowledge support from
the Portuguese Foundation for Science and Technology
(PTDC/EPH-ARQ/4164/2014) and the FEDER-COMPETE 2020
project 016899. P.S. was supported by the FCT Investigator Program
(IF/01641/2013), FCT IP, and ERDF (COMPETE2020 POCI).
M.Si. and K.D. were supported by a Leverhulme Trust Doctoral
Scholarship awarded to M.B.R. and M.P. D.R. was supported by
an Allen Discovery Center grant from the Paul Allen Foundation,
NIH grant GM100233, and the Howard Hughes Medical Institute.
V.V.-M. and W.H. were supported by the Max Planck Society.
Authors contributions: N.R., N.A., N.B., O.C., B.J.C., D.F., A.M.L.,
M.M., J.O., K.S., Z.Z., M.Si., K.D., C.J.E., D.J.K., M.B.R., W.H., R.P.,
and D.R. performed or supervised laboratory work. J.M.J.A., I.J.T.M.,
D.C.S.-G., P.C., M.Sa., J.T., M.L., J.F.-E., J.A.M.-A., C.Ba., F.J.B.,
J.B., N.C., E.V.M., D.V., A.C., J.M.F., O.G.-P., J.I.M., F.X.O., J.M.V.,
A.D.-C., I.O.-C., P.G.B., A.M.S., C.A.-F., J.J.E., A.M.-M., P.R.-G., J.R.M.,
E.V.V., K.T.L., J.M., A.W., G.D., B.A., F.C., A.Esp., G.d.P., A.Est.,
C.F., G.F., S.F., F.G.-G., T.M., A.R., J.V.-V., G.A.A., V.B.G., L.B.d.L.E.,
M.B.S., G.G.A., M.S.H.P., A.L., Y.C.M., I.C.B., A.F.F., D.L.-S., M.S.T.,
A.C.V., C.Bl., J.D., M.J.d.P.M., A.A.D.-C., R.F.F., J.F.F., R.G.-P.,
V.S.G., E.G.-D., A.M.H.-C., J.J.-C., C.L., F.J.L.-C., D.L.-R., S.B.M.,
M.M.P., A.O.F., G.P.B., P.R., M.S.B., A.C.S., J.M.V.E., M.Si., M.B.R.,
K.W.A., W.H., R.P., C.L.-F., and D.R. assembled archaeological
material. I.O., S.M., N.P., M.F.-B., V.V.-M., M.Si., C.J.E., F.G., M.P.,
P.S., and D.R. analyzed data. I.O., C.L.-F., and D.R. wrote the
manuscript. Competing interests: The authors declare no
competing interests. Data and materials availability: Sequencing
data are available from the European Nucleotide Archive,
accession PRJEB30874; genotype dataset is available as
supplementary material.
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Figs. S1 to S11
Tables S1 to S22
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Genotype Dataset
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10.1126/science.aav4040
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(6432), 1230-1234.363Science
, this issue p. 1230; see also p. 1153Science
present elucidate the genetic impact of prehistoric and historic migrations from Europe and North Africa.
Linguistics analysis and genetic analysis of archaeological human remains dating from about 7000 years ago to the
(see the Perspective by Vander Linden). The findings provide a comprehensive genetic time transect of the region.
report genome-wide data from 271 ancient individuals from Iberiaet al.globe. Focusing on the Iberian Peninsula, Olalde
Ancient DNA studies have begun to help us understand the genetic history and movements of people across the
Genomics of the Iberian Peninsula
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... BC by populations originating in the Middle East (Martins et al., 2015;Zilhão, 2000Zilhão, , 2001. This change in mode of subsistence is associated with marked genetic discontinuity between Iberian Mesolithic and Neolithic populations and substantial replacement of the former by the latter, despite some degree of population admixture (Haak et al., 2015;Olalde et al., 2015Olalde et al., , 2019Villalba-Mouco et al., 2019). Moreover, bone adapts to various aspects of mechanical loading (Currey, 2006;Judex & Rubin, 2010;Judex, Gross, & Zernicke, 1997;Judex, Lei, Han, & Rubin, 2007;Lanyon & Rubin, 1984;Lanyon, 1984;Mosley & Lanyon, 1998;Mosley, March, Lynch, & Lanyon, 1997;Turner, 1998) and so several previous studies have demonstrated that the dietary changes that occurred in the Mesolithic -Neolithic transition impacted mandibular morphology (Galland et al., 2016;Pokhojaev et al., 2019;von Cramon-Taubadel, 2011). ...
... BC by populations originating in the Middle East (Martins et al., 2015;Zilhão, 2000Zilhão, , 2001. This change in mode of subsistence is associated with marked genetic discontinuity between Iberian Mesolithic and Neolithic populations and substantial replacement of the former by the latter, despite some degree of population admixture (Haak et al., 2015;Olalde et al., 2015Olalde et al., , 2019Villalba-Mouco et al., 2019). Moreover, bone adapts to various aspects of mechanical loading (Currey, 2006;Judex & Rubin, 2010;Judex, Gross, & Zernicke, 1997;Judex, Lei, Han, & Rubin, 2007;Lanyon & Rubin, 1984;Lanyon, 1984;Mosley & Lanyon, 1998;Mosley, March, Lynch, & Lanyon, 1997;Turner, 1998) and so several previous studies have demonstrated that the dietary changes that occurred in the Mesolithic -Neolithic transition impacted mandibular morphology (Galland et al., 2016;Pokhojaev et al., 2019;von Cramon-Taubadel, 2011). ...
... Ancient DNA studies show marked genetic discontinuity between Mesolithic hunter-gatherers and Neolithic agro-pastoralists, thus suggesting population replacement mainly in most European regions. However, such studies also show the presence of Mesolithic DNA in post-Mesolithic individuals and so at least some level of admixture exists between the local Mesolithic and the incoming Neolithic populations (Haak et al., 2015;Olalde et al., 2015Olalde et al., , 2019Villalba-Mouco et al., 2019). Because mandibular morphology is known to relate to population history (Buck & Vidarsdottir, 2004;Katz et al., 2017;Mounier et al., 2018), our results showing shape differences between the two samples are to be expected and likely also related to population history. ...
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Human skeletal remains are routinely used to examine cultural and biological aspects of past populations. Yet, archaeological specimens are frequently fragmented/incomplete and so excluded from analyses. This leads to decreased sample sizes and to potentially biased results. Digital methods are now frequently used to restore/estimate the original morphology of fragmented/incomplete specimens. Such methods include 3D digitisation and Geometric Morphometrics (GM). The latter is also a solidly established method now to examine morphology. In this study, we use GM-based methods to estimate the original morphology of incomplete Mesolithic and Chalcolithic mandibles originating from present Portugal and perform ensuing morphological analyses. Because mandibular morphology is known to relate to population history and diet, we hypothesised the two samples would differ. Thirty-seven specimens (12 complete and 25 incomplete) were CT-scanned and landmarked. Originally complete specimens were used as reference to estimate the location of absent anatomical landmarks in incomplete specimens. As predicted, our results show shape differences between the two samples which are likely due to the compounded effect of contrasting population histories and diets.
... DNA. Genome-wide data from six individuals from Campo de Hockey were generated as part of this project (Olalde et al. 39 ) and can be downloaded from the European Nucleotide Archive database (accession PRJEB30874). Three individuals yielded a better DNA preservation and between ~ 260,000-660,000 autosomal genetic markers (SNPs) could be recovered, while the remaining three yielded less than 100,000 markers. ...
... First, the mismatch rate at autosomal markers for each pair of individuals was computed, by randomly sampling one www.nature.com/scientificreports/ reading at each SNP for each individual 39,41,42 . Then, we normalized these values by the mismatch rate expected for two unrelated Iberian Neolithic individuals and estimated the coefficient of relatedness (equivalent to the portion of the genome being shared) using the method used by Kennett et al. 41 and Olalde et al. 39 . ...
... reading at each SNP for each individual 39,41,42 . Then, we normalized these values by the mismatch rate expected for two unrelated Iberian Neolithic individuals and estimated the coefficient of relatedness (equivalent to the portion of the genome being shared) using the method used by Kennett et al. 41 and Olalde et al. 39 . ...
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... Here it also has to be kept in mind that not only an exchange of objects has been documented, but that anthropological DNA analysis made in Camino de Yeseras seems to confi rm an occasional movement of people of African origin (Olalde et al. 2019;Liesau/Blasco 2019). ...
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En la primera década del siglo XXI se efectuó en Alcalá del Río (Sevilla) una serie de intervenciones arqueológicas en las que se detectaron los restos correspondientes a un poblado y a una necrópolis de época tartésica. La presente obra, aunque se centra en el análisis de los enterramientos, incorpora también la información recuperada en la zona de hábitat, al considerar ambos enclaves como partes integrantes de un mismo asentamiento. El trabajo se inicia con una contextualización de las sepulturas en el marco de la relación poblado-necrópolis, atendiendo al patrón de asentamiento, su relación espacio-temporal y la ubicación del cementerio en su contexto paleogeográfico. A partir de esta exposición se realiza un estudio centrado en la configuración general de la necrópolis y la distribución de las tumbas. El tercer nivel de análisis se ocupa de la investigación específica de cada sepultura y de los distintos elementos depositados en su interior, principalmente de los ajuares. Estos estudios se completan con una serie de análisis sobre antropología física y paleopatología, paleodieta, ADN, antracología, etc., cuyos resultados posibilitan la reconstrucción de los ritos funerarios y un acercamiento a la caracterización de la población enterrada, su hábitat y otros aspectos relativos a sus estrategias de explotación y adaptación al medio. En definitiva, los datos aportados por la excavación de la necrópolis de la Angorrilla, junto con las investigaciones desarrolladas en el poblado coetáneo, contribuyen al conocimiento de las comunidades que ocupaban el Bajo Guadalquivir durante el Hierro I, convirtiendo a este yacimiento en uno de los referentes fundamentales para caracterizar a dichas poblaciones y valorar cómo influyó la colonización oriental en este espacio geográfico.
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The Cueva del Angel archaeological site is an open-air sedimentary sequence, remnant of a collapsed cave and part of a karst complex. The faunal assemblage dominated by Equus ferus, large bovids and cervids has been subjected to intense anthropic actions reflecting selective predation. The fauna may be correlated with European faunistic associations of the end of the Middle Pleistocene to the beginning of the Upper Pleistocene. The Cueva del Angel lithic assemblage (dominated by non-modified flakes and abundant retouched tools with the presence of 46 handaxes) appears to fit well within the regional diversity of a well developed non-Levallois final Acheulean industry. A preliminary 230 Th/ 234 U age estimate, the review of the lithic assemblage and faunal evidence would favour a chronological positioning of the site in a period stretching from the end of the Middle Pleistocene to the beginning of the Upper Pleistocene (MIS 11eMIS 5). The Acheulean lithic assemblage found at the Cueva del Angel fits very well with the hypothesis of a continuation of Acheulean cultural traditions in the site, distinct from the contemporaneous uniquely Mousterian complexes witnessed in other parts of the Iberian Peninsula, and Western Europe.
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The Iberian Peninsula is linguistically diverse and has a complex demographic history, including a centuries-long period of Muslim rule. Here, we study the fine-scale genetic structure of its population, and the genetic impacts of historical events, leveraging powerful, haplotype-based statistical methods to analyse 1413 individuals from across Spain. We detect extensive fine-scale population structure at extremely fine scales (below 10 Km) in some regions, including Galicia. We identify a major east-west axis of genetic differentiation, and evidence of historical north to south population movement. We find regionally varying fractions of north-west African ancestry (0–11%) in modern-day Iberians, related to an admixture event involving European-like and north-west African-like source populations. We date this event to 860–1120 CE, implying greater genetic impacts in the early half of Muslim rule in Iberia. Together, our results indicate clear genetic impacts of population movements associated with both the Muslim conquest and the subsequent Reconquista.
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The extent to which prehistoric migrations of farmers influenced the genetic pool of western North Africans remains unclear. Archaeological evidence suggests that the Neolithization process may have happened through the adoption of innovations by local Epipaleolithic communities or by demic diffusion from the Eastern Mediterranean shores or Iberia. Here, we present an analysis of individuals' genome sequences from Early and Late Neolithic sites in Morocco and from Early Neolithic individuals from southern Iberia. We show that Early Neolithic Moroccans (∼5,000 BCE) are similar to Later Stone Age individuals from the same region and possess an endemic element retained in present-day Maghrebi populations, confirming a long-term genetic continuity in the region. This scenario is consistent with Early Neolithic traditions in North Africa deriving from Epipaleolithic communities that adopted certain agricultural techniques from neighboring populations. Among Eurasian ancient populations, Early Neolithic Moroccans are distantly related to Levantine Natufian hunter-gatherers (∼9,000 BCE) and Pre-Pottery Neolithic farmers (∼6,500 BCE). Late Neolithic (∼3,000 BCE) Moroccans, in contrast, share an Iberian component, supporting theories of trans-Gibraltar gene flow and indicating that Neolithization of North Africa involved both the movement of ideas and people. Lastly, the southern Iberian Early Neolithic samples share the same genetic composition as the Cardial Mediterranean Neolithic culture that reached Iberia ∼5,500 BCE. The cultural and genetic similarities between Iberian and North African Neolithic traditions further reinforce the model of an Iberian migration into the Maghreb.
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We applied taphonomic analysis combined with geostatistical approaches to investigate the hypothesis that Cocina cave (Eastern Iberia) represents an acculturation context for the appearance of Neolithic Cardial pottery. In the 1970s, Fortea suggested that this important site was a prime example of acculturation because of the presence of early Neolithic pottery in late Mesolithic contexts. Since that time Cocina cave has been heralded as an example of indigenous hunter-gatherers incorporating Neolithic cultural elements into their lifeways. We analyzed the area excavated by Fortea in the 1970s by digitizing archaeological records and testing the spatial distribution of artifacts using geostatistical analysis and high-resolution AMS radiocarbon dating. We contextualized the findings by discussing key issues of archaeological depositions with the goal to better understand the palimpsest that usually occur in prehistoric sequences. Our analysis indicates that the mixture of Mesolithic and Neolithic materials resulted from taphonomic processes rather than acculturation.
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Archaeogenomic research has proven to be a valuable tool to trace migrations of historic and prehistoric individuals and groups, whereas relationships within a group or burial site have not been investigated to a large extent. Knowing the genetic kinship of historic and prehistoric individuals would give important insights into social structures of ancient and historic cultures. Most archaeogenetic research concerning kinship has been restricted to uniparental markers, while studies using genome-wide information were mainly focused on comparisons between populations. Applications which infer the degree of relationship based on modern-day DNA information typically require diploid genotype data. Low concentration of endogenous DNA, fragmentation and other post-mortem damage to ancient DNA (aDNA) makes the application of such tools unfeasible for most archaeological samples. To infer family relationships for degraded samples, we developed the software READ (Relationship Estimation from Ancient DNA). We show that our heuristic approach can successfully infer up to second degree relationships with as little as 0.1x shotgun coverage per genome for pairs of individuals. We uncover previously unknown relationships among prehistoric individuals by applying READ to published aDNA data from several human remains excavated from different cultural contexts. In particular, we find a group of five closely related males from the same Corded Ware culture site in modern-day Germany, suggesting patrilocality, which highlights the possibility to uncover social structures of ancient populations by applying READ to genome-wide aDNA data. READ is publicly available from https://bitbucket.org/tguenther/read.
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We describe a simple method for extracting polymerase chain reaction‐amplifiable DNA from ancient bones without the use of organic solvents. Bone powders are digested with proteinase K, and the DNA is purified directly using silica‐based spin columns (QIAquick™, QIAGEN). The efficiency of this protocol is demonstrated using human bone samples ranging in age from 15 to 5,000 years old. Am J Phys Anthropol 105:539–543, 1998. © 1998 Wiley‐Liss, Inc.
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Noonan syndrome (NS), the most common RASopathy, is caused by mutations affecting signaling through RAS and the MAPK cascade. Recently, genome scanning has discovered novel genes implicated in NS, whose function in RAS-MAPK signaling remains obscure, suggesting the existence of unrecognized circuits contributing to signal modulation in this pathway. Among these genes, LZTR1 encodes a functionally poorly characterized member of the BTB/POZ protein superfamily. Two classes of germline LZTR1 mutations underlie dominant and recessive forms of NS, while constitutional monoallelic, mostly inactivating, mutations in the same gene cause schwannomatosis, a cancer-prone disorder clinically distinct from NS. Here we show that dominant NS-causing LZTR1 mutations do not affect significantly protein stability and subcellular localization. We provide the first evidence that these mutations, but not the missense changes occurring as biallelic mutations in recessive NS, enhance stimulus-dependent RAS-MAPK signaling, which is triggered, at least in part, by an increased RAS protein pool. Moreover, we document that dominant NS-causing mutations do not perturb binding of LZTR1 to CUL3, a scaffold coordinating the assembly of a multimeric complex catalyzing protein ubiquitination, but are predicted to affect the surface of the Kelch domain mediating substrate binding to the complex. Collectively, our data suggest a model in which LZTR1 contributes to the ubiquitination of protein(s) functioning as positive modulator(s) of the RAS-MAPK signaling pathway. In this model, LZTR1 mutations are predicted to variably impair binding of these substrates to the multi-component ligase complex and their efficient ubiquitination and degradation, resulting in MAPK signaling upregulation.